Immunocompromised (AIDS) patients with opportunistic fungal infections frequently suffer high morbidity (>70%) and mortality in spite of therapy, due to a lack of therapeutic efficacy or toxicity, and resistance to currently available agents. The goal of this project is to enhance antimycotic drug discovery by integrating information and compounds derived from traditional antifungal discovery with a pharmacogenomics approach. Our first two objectives will be to identify pharmacogenomic characteristics of natural products and FDA approved drugs with antifungal activity. These comparative pharmacogenomic screenings will focus on eukaryotic cell (human) toxicity and activity in pathogenic fungi. Traditional drug development processes utilize batteries of acute and chronic toxicity tests to evaluate safety. However, this approach is time consuming, costly in terms of animal life, and often not predictive. Pharmacogenomics is an efficient tool, permitting measurements of differentially expressed genes from eukaryotic cells exposed to antifungal agents. The differential expression observed in hundreds to thousands of genes can suggest how a compound affects cellular processes. The cellular processes of "signatures" will be used to more efficiently direct biochemical and animal testing in the NCNPR. Our third objective is to establish a database of "signatures" and develop a model that is predictive of a novel agent's behavior. Confirmation of the mechanism of action and the identification of undesirable secondary effects in man are among the main challenges in developing new drugs. A database of transcriptional behaviors or "signatures" for antimycotic compounds can be modeled with biochemical, pharmacological and toxicological data to predict outcomes of new agents. Recognition of potential toxicities in the signatures of otherwise promising compounds may allow earlier identification of those likely to fail in clinical trials or allow investigators to focus preclinical investigations. Recognition of agents with new mechanisms of action against mycotic organisms is also a potential benefit. Comparing the extent and peculiarities of "off-target" signatures of promising drug candidates could provide insight into indications for an unrelated diagnoses. A long-term benefit of our model should include the development of a "therapeutic array" which could be developed from our model. This array would contain mainly transcripts from various tissue sites and yeast. Probing this array with eukaryotic mRNA from cells exposed to novel antifungals would predict common mechanism of action and likelihood of toxicity, activity and resistance.